Clay Theo J, Da Custodia Steel Zephy J, Jacobs Chris
Medical Education, University of Bristol, Bristol, GBR.
Psychology, University of Bath, Bath, GBR.
Cureus. 2024 Nov 15;16(11):e73763. doi: 10.7759/cureus.73763. eCollection 2024 Nov.
The integration of artificial intelligence (AI) into healthcare communication has rapidly evolved, driven by advancements in large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT). This literature review explores AI's role in patient-physician interactions, particularly focusing on its capacity to enhance communication by bridging language barriers, summarizing complex medical data, and offering empathetic responses. AI's strengths lie in its ability to deliver comprehensible, concise, and medically accurate information. Studies indicate AI can outperform human physicians in certain communicative aspects, such as empathy and clarity, with models like ChatGPT and the Medical Pathways Language Model (Med-PaLM) demonstrating high effectiveness in these areas. However, significant challenges remain, including occasional inaccuracies and "hallucinations," where AI-generated content is irrelevant or medically inaccurate. These limitations highlight the need for continued refinement in AI algorithms to ensure reliability and consistency in sensitive healthcare settings. The review underscores the potential of AI as a transformative tool in health communication while advocating for further research and policy development to mitigate risks and enhance AI's integration into clinical practice.
在诸如聊天生成预训练变换器(ChatGPT)等大语言模型(LLMs)进步的推动下,人工智能(AI)在医疗保健沟通中的整合迅速发展。这篇文献综述探讨了AI在医患互动中的作用,尤其关注其通过消除语言障碍、总结复杂医学数据以及提供共情回应来加强沟通的能力。AI的优势在于能够提供可理解、简洁且医学上准确的信息。研究表明,在某些沟通方面,如共情和清晰度,AI可以胜过人类医生,像ChatGPT和医学路径语言模型(Med-PaLM)等模型在这些领域展现出了高效能。然而,重大挑战依然存在,包括偶尔出现的不准确和“幻觉”情况,即AI生成的内容不相关或医学上不准确。这些局限性凸显了持续优化AI算法的必要性,以确保在敏感的医疗环境中的可靠性和一致性。该综述强调了AI作为健康沟通中变革性工具的潜力,同时倡导进一步开展研究和制定政策,以降低风险并加强AI在临床实践中的整合。